Uber is expanding AI deployment across its logistics and mobility network as the company pushes deeper into real-time automation, freight intelligence and voice-based ride support.

Uber’s AI systems are now being used across driver assistance, freight management and rider support operations spanning more than 15,000 cities in over 70 countries.

The progress signals a wider industry shift as global transport and supply chain firms invest heavily in AI-led logistics platforms to improve productivity, reduce delays and automate routine tasks.

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Uber Deploys AI Tools for Drivers, Riders and Freight Networks

Uber has introduced an in-app AI assistant for drivers that converts live marketplace data into real-time suggestions on positioning, demand zones and earning opportunities. The system uses local pricing trends, traffic signals and demand forecasts to generate city-specific guidance for drivers.

For riders, Uber has introduced a voice-enabled AI interface backed by OpenAI’s Real-time Application Programming Interface (API). It can process more complex spoken ride requests, including airport pickups involving multiple luggage items or saved destinations.

The company has also integrated AI deeper into its freight and transportation management systems through Uber Freight. Its logistics platform now includes more than 30 AI agents handling shipment execution, procurement, tracking, analytics and payments. The system is designed to help shippers automate repetitive tasks and improve supply chain visibility.

Uber Freight said its AI tools are powered by a logistics-specific large language model developed internally and embedded directly into its transportation management system.

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“Our internal AI-Guard system reviews prompts and responses to ensure safety, privacy and policy compliance before outputs reach users.”

-said Uber officials

Company executives have further stressed that trust and reliability remain central as AI becomes more integrated into transportation systems.

The company is also expanding partnerships in autonomous driving, cloud infrastructure and AI data operations. Recent initiatives include broader cloud collaboration with Amazon Web Services (AWS), autonomous-vehicle partnerships with NVIDIA and Nuro and experiments in AI data collection and annotation through its driver ecosystem.

Industry analysts say AI adoption in logistics is accelerating as companies seek to reduce operational inefficiencies, improve delivery accuracy, and manage increasingly complex supply chains. Competitors across freight, mobility and logistics technology are also investing heavily in automation and predictive AI tools.